BackgroundIncreasing evidence has proven that rheumatoid arthritis (RA) can aggravate atherosclerosis (AS), and we aimed to explore potential diagnostic genes for patients with AS and RA.MethodsWe obtained the data from public databases, including Gene Expression Omnibus (GEO) and STRING, and obtained the differentially expressed genes (DEGs) and module genes with Limma and weighted gene co-expression network analysis (WGCNA). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis, the protein–protein interaction (PPI) network, and machine learning algorithms [least absolute shrinkage and selection operator (LASSO) regression and random forest] were performed to explore the immune-related hub genes. We used a nomogram and receiver operating characteristic (ROC) curve to assess the diagnostic efficacy, which has been validated with GSE55235 and GSE73754. Finally, immune infiltration was developed in AS.ResultsThe AS dataset included 5,322 DEGs, while there were 1,439 DEGs and 206 module genes in RA. The intersection of DEGs for AS and crucial genes for RA was 53, which were involved in immunity. After the PPI network and machine learning construction, six hub genes were used for the construction of a nomogram and for diagnostic efficacy assessment, which showed great diagnostic value (area under the curve from 0.723 to 1). Immune infiltration also revealed the disorder of immunocytes.ConclusionSix immune-related hub genes (NFIL3, EED, GRK2, MAP3K11, RMI1, and TPST1) were recognized, and the nomogram was developed for AS with RA diagnosis.

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Adolescent idiopathic scoliosis (AIS) is a common chronic disease in youths, presenting with spinal deformity. Previous studies reported that the family functioning of family members would be affected after a child is diagnosed with a chronic health condition. However, no previous study focused on the relationship between AIS and family function. This study is a cross-sectional study that enrolled 54 AIS families and 92 ordinary families and evaluated their family function in 7 domains using the McMaster family assessment device (FAD). The results showed that the AIS family got a lower score than a healthy family in all 7 subscales except for the problem-solving subscale. There was no significant difference between the patients with AIS (1.90 ± 0.42∼2.23 ± 0.32) and their parents (1.92 ± 0.35∼2.21 ± 0.29) in all seven subscales (p ≥ 0.05). The scores of the parents were moderately/strongly correlated with those of the patients with AIS in all seven subscales (γ = 0.456∼0.696, p < 0.05). Approximately, 20.4–87% of the families experienced unhealthy family functioning, with affective involvement (57.4%), and behavior control (87%) representing the unhealthiest subscales with the mean scores above the cutoff. It can be concluded that the AIS family performed better than a healthy family in family functions.

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